Package: heteromixgm 2.0.2

Sjoerd Hermes

heteromixgm: Copula Graphical Models for Heterogeneous Mixed Data

A multi-core R package that allows for the statistical modeling of multi-group multivariate mixed data using Gaussian graphical models. Combining the Gaussian copula framework with the fused graphical lasso penalty, the 'heteromixgm' package can handle a wide variety of datasets found in various sciences. The package also includes an option to perform model selection using the AIC, BIC and EBIC information criteria, a function that plots partial correlation graphs based on the selected precision matrices, as well as simulate mixed heterogeneous data for exploratory or simulation purposes and one multi-group multivariate mixed agricultural dataset pertaining to maize yields. The package implements the methodological developments found in Hermes et al. (2024) <doi:10.1080/10618600.2023.2289545>.

Authors:Sjoerd Hermes [aut, cre], Joost van Heerwaarden [ctb], Pariya Behrouzi [ctb]

heteromixgm_2.0.2.tar.gz
heteromixgm_2.0.2.tar.gz(r-4.5-noble)heteromixgm_2.0.2.tar.gz(r-4.4-noble)
heteromixgm_2.0.2.tgz(r-4.4-emscripten)heteromixgm_2.0.2.tgz(r-4.3-emscripten)
heteromixgm.pdf |heteromixgm.html✨
heteromixgm/json (API)

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6 exports 0.09 score 40 dependencies 483 downloads

Last updated 29 days agofrom:10d12c3706. Checks:OK: 2. Indexed: yes.

Exports:data_simheteromixgminitializelower.uppermodselectplot_pcorgraph

Dependencies:BDgraphclicolorspacecpp11fansifarverggplot2glassogluegmmgtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellmvtnormnlmepillarpkgconfigplyrpROCR6RColorBrewerRcpprlangsandwichscalestibbletmvtnormutf8vctrsviridisLitewithrzoo